The purpose of this study is to examine the effect of missing data imputation methods, namely regression imputation (RI), multiple imputation (MI) and k-nearest neighbor (kNN) on differential item functioning (DIF). In this regard, the datasets used in the research were created by deleting some of the data via the missing completely at random…

As scientific literacy plays a contributing role in identifying, analysing, and solving environmental matters that our world is facing, there is growing consensus to mandate environmental matters in science classrooms following five decades of efforts in promoting environmental education. However, much remains unknown about the relationship…

Efficiency in reading component skills is crucial for reading comprehension, as efficient subprocesses do not extensively consume limited cognitive resources, making them available for comprehension processes. Cognitive efficiency is typically measured with speeded tests of relatively easy items. Observed responses and response times indicate the…

Exploring the relationship between student ability and test-taking effort is an important area of study, offering insights into their approach to educational assessments. Previous research shows this relationship, yet there is a scarcity of research comparing the test-taking effort of students. In addition, researchers have frequently employed…

This study utilizes the 2015 data from the Hong Kong sample of the Program for International Student Assessment to examine the relative importance of various factors on the science learning performance of Hong Kong students. Using hierarchical linear modeling (HLM), we examined the effect of students' affective characteristics, involvement, and…

Previous research on the implications of early-tracking education systems has not specifically focused on how studying in academic and non-academic tracks shapes the features and characteristics of shadow education (private tutoring) that students are involved in. The study compares the scale and features of private tutoring and the underlying…

The purpose of this study is to identify to what extent that the reading comprehension, question types, attitude toward science, test method, and subject matter knowledge predict the PISA scientific literacy scores of the students. The study uses the method of correlational research, which is a type of quantitative research method. We reached out…

Position effects (PE) cause decreasing probabilities of correct item responses towards the end of a test. We analysed PEs in science, mathematics and reading tests administered in the German extension to the PISA 2006 study with respect to their variability at the student- and school-level. PEs were strongest in reading and weakest in mathematics.…

Background: Life satisfaction is a key component of students' subjective well-being due to its impact on academic achievement and lifelong health. Although previous studies have investigated life satisfaction through different lenses, few of them employed machine learning (ML) approaches. Objective: Using ML algorithms, the current study predicts…

This study aims to investigate the predictors of reading performance and how reading performance predicts mathematics and science performances in PISA 2018 study. For this purpose, the country in the focus (Turkey), the highest performer (China [B-S-J-Z]) in the world, and the lowest performer (Mexico) among the OECD members countries were…

This study examines the relationship between instructional quality and mathematics achievement, taking into account socioeconomic status. Data from ten European countries participating in PISA 2012 and 2022 were analysed using the framework of the Dynamic Modelling of Educational Effectiveness. In PISA 2012, instructional quality was defined by…

The issue of model uncertainty has been gaining interest in education and the social sciences community over the years, and the dominant methods for handling model uncertainty are based on Bayesian inference, particularly, Bayesian model averaging. However, Bayesian model averaging assumes that the true data-generating model is within the…

The concept of growth mindset has been touted as a promising tool to empower learning, but mixed effects emerge. Growth mindset advocates are calling for more attention to the heterogeneity of growth mindset, namely, the interference of other factors at individual or contextual levels (e.g., teacher variables) with the relationship between growth…

Brazil's education system lags behind international standards, with two-fifths of students scoring below the minimum level of proficiency in mathematics, science, and reading. Thus, this study combined machine learning with traditional statistics to identify the most important predictors and to interpret their effects on proficiency in the PISA…

This study explores structural relations among learning environment, achievement goals and reading achievement in China. The sample contains 12,058 Chinese students from the Programme for International Student Assessment (PISA) 2018 study. Multilevel Structural Equation Modeling (Multilevel SEM) is used for data analysis. The results indicate that…